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Introduction to Artificial Intelligence

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1 Introduction to Artificial Intelligence
Dr. Sunil Kumar

2 Contents Artificial Intelligence Characterstics of AI Program
Categories of System Turing Test Foundations of AI Views of AI Goals Components of AI Programs Sub-areas of AI Applications Latest Perception of AI Dr. Sunil Kumar

3 Artificial Intelligence
Quick Answer from Academia: Modeling human cognition or mental faculty using computers Study of making computers do things which at the moment people better Making computers do things which require intelligence Dr. Sunil Kumar

4 More Formal Definition of AI
AI is a branch of computer science which is concerned with the study and creation of computer systems that exhibit some form of intelligence OR those characteristics which we associate with intelligence in human behavior Dr. Sunil Kumar

5 What is Intelligence? Intelligence is a property of mind that encompasses many related mental abilities, such as the capabilities to reason plan solve problems think abstractly comprehend ideas and language and learn Dr. Sunil Kumar

6 Characteristics of AI systems
learn new concepts and tasks reason and draw useful conclusions about the world around us remember complicated interrelated facts and draw conclusions from them (inference) understand a natural language or perceive and comprehend a visual scene look through cameras and see what's there (vision), to move themselves and objects around in the real world (robotics) Dr. Sunil Kumar

7 Contd.. plan sequences of actions to complete a goal
offer advice based on rules and situations may not necessarily imitate human senses and thought processes but indeed, in performing some tasks differently, they may actually exceed human abilities capable of performing intelligent tasks effectively and efficiently perform tasks that require high levels of intelligence Dr. Sunil Kumar

8 Boundaries of AI are not well defined.
Artificial intelligence is also difficult to understand by its content. Boundaries of AI are not well defined. Often it means the advanced software engineering, sophisticated software techniques for hard problems that can't be solved in any easy way. AI programs - like people - are usually not perfect, and even make mistakes. Dr. Sunil Kumar

9 Categories of AI System
Systems that think like humans Systems that act like humans Systems that think rationally Systems that act rationally Dr. Sunil Kumar

10 Systems that think like humans
Most of the time it is a black box where we are not clear about our thought process. One has to know functioning of brain and its mechanism for possessing information. It is an area of cognitive science. The stimuli are converted into mental representation. Cognitive processes manipulate representation to build new representations that are used to generate actions. Neural network is a computing model for processing information similar to brain. Dr. Sunil Kumar

11 Systems that act like humans
The overall behavior of the system should be human like. It could be achieved by observation. Dr. Sunil Kumar

12 Systems that think rationally
Such systems rely on logic rather than human to measure correctness. For thinking rationally or logically, logic formulas and theories are used for synthesizing outcomes. For example, given John is a human and all humans are mortal then one can conclude logically that John is mortal Not all intelligent behavior are mediated by logical deliberation. Dr. Sunil Kumar

13 Systems that act rationally
Rational behavior means doing right thing. Even if method is illogical, the observed behavior must be rational. Dr. Sunil Kumar

14 The Turing Test Turing proposed operational test for intelligent behavior in Human Human ? Interrogator AI system Dr. Sunil Kumar

15 ELIZA Eliza was first program developed by Joseph Wiezbaum to converse in English in mid 1960's It passed turing test. The following passage shows Eliza’s talking to a teenage girl. Blue text Eliza’s response Men are all alike. IN WHAT WAY They're always bugging us about something or other. CAN YOU THINK OF A SPECIFIC EXAMPLE Dr. Sunil Kumar

16 Well, my boyfriend made me come here.
YOUR BOYFRIEND MADE YOU COME HERE He says that I am depressed all the time. I AM SORRY TO HEAR THAT YOU ARE DEPRESSED It's true that I am unhappy DO YOU THINK COMING HERE WILL HELP YOU NOT TO BE UNHAPPY I need help, that seems certain. WHAT WOULD IT MEAN IF YOU GOT SOME HELP Perhaps I could learn to get along with my mother. TELL ME MORE ABOUT YOUR FAMILY Dr. Sunil Kumar

17 My mother takes care of me. WHO ELSE IN YOUR FAMILY TAKES CARE OF YOU
My father. YOUR FATHER You are like my father in some ways. WHAT RESEMBLANCE DO YOU SEE You are not very aggressive but I think you don't want me to notice that. WHAT MAKES YOU THINK THAT I AM NOT VERY AGGRESSIVE Dr. Sunil Kumar

18 WHY DO YOU THINK I DON’T ARGUE WITH YOU You are afraid of me.
You don’t argue with me. WHY DO YOU THINK I DON’T ARGUE WITH YOU You are afraid of me. DOES IT PLEASE YOU TO BELIEVE, I AM AFRAID OF YOU My father is afraid of everybody. WHAT ELSE COMES TO MIND WHEN YOU THINK OF YOUR FATHER Bullies. DOES THAT HAVE ANYTHING TO DO WITH THE FACT THAT YOUR BOYFRIEND MADE YOU COME HERE Dr. Sunil Kumar

19 Foundations of AI Foundation of AI is based on Mathematics
Neuroscience Control Theory Linguistics Dr. Sunil Kumar

20 Components of AI Program
AI techniques must be independent of the problem domain as far as possible. AI program should have knowledge base navigational capability inferencing Dr. Sunil Kumar

21 Knowledge Base AI programs should be learning in nature and update its knowledge accordingly. Knowledge base consists of facts and rules. Characteristics of Knowledge: It is voluminous in nature and requires proper structuring It may be incomplete and imprecise It may keep on changing (dynamic) Dr. Sunil Kumar

22 Navigational Capability
Navigational capability contains various control strategies Control Strategy determines the rule to be applied some heuristics (thump rule) may be applied Dr. Sunil Kumar

23 Inferencing Inferencing requires search through knowledge base and
derive new knowledge Dr. Sunil Kumar

24 Sub-areas of AI Sub areas of AI are: Knowledge representation
Theorem proving Game playing Vommon sense reasoning dealing with uncertainty and decision making Learning models, inference techniques, pattern recognition, search and matching etc. Logic (fuzzy, temporal, modal) in AI Planning and scheduling Dr. Sunil Kumar

25 Sub-areas of AI – Contd.. Natural language understanding
Computer vision Understanding spoken utterances Intelligent tutoring systems Robotics Machine translation systems Expert problem solving Neural Networks, AI tools etc Dr. Sunil Kumar

26 Applications Some of the applications are given below:
Business : Financial strategies, give advice Engineering: check design, offer suggestions to create new product Manufacturing: Assembly, inspection & maintenance Mining: used when conditions are dangerous Hospital : monitoring, diagnosing & prescribing Education : In teaching household : Advice on cooking, shopping etc. farming : prune trees & selectively harvest mixed crops. Dr. Sunil Kumar


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